tanstack-query

A guide to TanStack Query v5, a React library for loading, caching, updating, and reusing data from APIs.

In plain words
What is it for?
Use it when working with queries, mutations, prefetching, infinite lists, Suspense, cache invalidation, or render performance.
Why use it?
It helps avoid incorrect cache settings, duplicated requests, slow request chains, and inefficient screen updates.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/pymodel/react-frontend-skills/tanstack-query
Any agent
npx skills add PyModel/react-frontend-skills --skill tanstack-query
Clone the repo
git clone --depth 1 https://github.com/PyModel/react-frontend-skills

Made for: Claude Code, Codex.

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,218 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.01218
Opus 5 $0.00032 $0.00609
Sonnet 5 $0.00013 $0.00244
Haiku 4.5 $0.00006 $0.00122

Measured 2d ago against content hash 31937db72f24, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

tanstack-query scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

86% identical to tanstack-query — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/tanstack-query/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TanStack Query Best Practices

Comprehensive performance optimization guide for TanStack Query v5 applications. Contains 40 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

When to Apply

Reference these guidelines when:

  • Writing new queries, mutations, or data fetching logic
  • Implementing caching strategies (staleTime, gcTime)
  • Reviewing code for performance issues or request waterfalls
  • Refactoring existing TanStack Query code
  • Implementing infinite queries, Suspense, or optimistic updates

Rule Categories by Priority

Priority Category Impact Prefix
1 Query Key Structure CRITICAL tquery-
2 Caching Configuration CRITICAL cache-
3 Mutation Patterns HIGH mutation-
4 Prefetching & Waterfalls HIGH prefetch-
5 Infinite Queries MEDIUM infinite-
6 Suspense Integration MEDIUM suspense-
7 Error & Retry Handling MEDIUM error-
8 Render Optimization LOW-MEDIUM render-

Quick Reference

1. Query Key Structure (CRITICAL)

  • tquery-key-factories - Use centralized query key factories
  • tquery-hierarchical-keys - Structure keys from generic to specific
  • tquery-always-arrays - Always use array query keys
  • tquery-serializable-objects - Use serializable objects in keys
  • tquery-options-pattern - Use queryOptions for type-safe sharing
  • tquery-colocate-keys - Colocate query keys with features

2. Caching Configuration (CRITICAL)

  • cache-staletime-gctime - Understand staleTime vs gcTime
  • cache-global-defaults - Configure global defaults appropriately
  • cache-placeholder-vs-initial - Use placeholderData vs initialData correctly
  • cache-invalidation-precision - Invalidate with precision
  • cache-refetch-triggers - Control automatic refetch triggers
  • cache-enabled-option - Use enabled or skipToken for conditional queries

3. Mutation Patterns (HIGH)

Read the full file on GitHub · 122 lines

Files

What ships with it

41 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 122 lines · 64 tokens per session scan A 31937db72f24

Subscribe to this mod's changes

tanstack-query is a skill published in the GitHub repository PyModel/react-frontend-skills (3 stars, last pushed 13d ago), licensed MIT. It adds 64 tokens to every session and 1,218 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to tanstack-query, differing in 18 lines, and is treated as a copy.

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